Principles of Econometrics with R
lmtest – R Functions and Packages for Political Science Analysis
Relaxing Assumptions of Classical - Heteroskedasticity - Relaxing Assumptions of Classical Model- - Studocu
sandwich: Robust Covariance Matrix Estimators • sandwich
Basic Time Series Models | SpringerLink
regression - R: Confused about robust standard errors using “felm” and “huxreg” - Cross Validated
lmtest – R Functions and Packages for Political Science Analysis
Robust and clustered standard errors with R | Program Evaluation
Group-By Modeling in R Made Easy | R-bloggers
augment and sandwich vcov? · Issue #237 · tidymodels/broom · GitHub
Dealing with heteroskedasticity; regression with robust standard errors using R
Robust and clustered standard errors with R | Program Evaluation
Column names: tidy() · Issue #455 · tidymodels/broom · GitHub
Quasi-Experimental Design: Natural Experiment and Instrumental Variable – Taiwo A. Ahmed
Robust and clustered standard errors with R | Program Evaluation
Enhancement: easy way to select rows from a tidy data frame · Issue #525 · tidymodels/broom · GitHub
Compatibility with stargazer or xtable · Issue #12 · tidymodels/broom · GitHub
Non-Constant Variance
robust standard errors: will tidy.coeftest(., conf.int=TRUE) ever be possible? · Issue #663 · tidymodels/broom · GitHub
Slides from my talk on the broom package – Variance Explained
Regression table with clustered standard errors in R jupyter notebook? - Stack Overflow
sandwich: Robust Covariance Matrix Estimators • sandwich
Principles of Econometrics with R
Slides from my talk on the broom package – Variance Explained
Robust and clustered standard errors with R | Program Evaluation
